Cardiovascular Outcomes in the Patients With Colorectal Cancer: A Multi-Registry-Based Cohort Study of 197,699 Cases in the Real World - Zhang, Shilong; Wang, Yan; Zhang, Pengfei; Ai, Luoyan; Liu, Tianshu (Frontiers in Cardiovascular Medicine, 2022)
Purpose: We aimed to investigate the mortality patterns and quantitatively assess the risks of cardiovascular death (CVD) in CRC patients. We also established a competing risk nomogram to predict the probability of CVD for CRC patients. Patients and Methods: The CRC patients diagnosed between 2007 and 2015 in the Surveillance, Epidemiology, and End Results (SEER) database were included in the present study. The cumulative incidence function (CIF) was used for CVD and other causes of death, and Gray’s test was used to determine the subgroup difference in CIF. The Fine-Gray proportional subdistribution hazards model was used for identifying independent risk factors for CVD. A novel competing risk nomogram was established to evaluate the probability of CVD for CRC patients. The performance of the nomogram was measured by concordance index (C-index), calibration curve, decision curve analysis (DCA), and risk stratification. Results: After a median follow-up of 37.00 months, 79455 deaths occurred, of whom 56185 (70.71%) succumbed to CRC, 23270 (29.29%) patients due to non-CRC, among which CVD accounted for 9702 (41.69%), being the major cause of non-cancer deaths. The 1-, 3- and 5-year cumulative rates for CVD were 12.20%, 24.25%, and 30.51%, respectively. In multivariate analysis, age, race, marital status, tumor size, tumor stage, advanced stage, surgery, and chemotherapy were independent risk factors of CVD among CRC patients. The nomogram was well calibrated, and had good discriminative ability, with a c-index of 0.719 (95%CI, 0.738-0.742) in the training cohort and 0.719 (95%CI, 0.622-0.668) in the validation cohort. DCA demonstrated that nomogram produced more benefit within wide ranges of threshold probabilities for 1-, 3-, and 5-year CVD, respectively. Conclusions: This study was the first to analyze the CIF and risk factors for CVD among CRC based on a competing-risks model. We have also built the first 1-, 3-, and 5-year competing nomogram for predicting CVD. This nomogram had excellent performance and could help clinicians to provide individualized management in clinical practice.